At present,the prevalence of diabetes is increasing because the human body cannot metabolize the glucose *** prediction of diabetes patients is an important research *** researchers have proposed techniques to predict...
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At present,the prevalence of diabetes is increasing because the human body cannot metabolize the glucose *** prediction of diabetes patients is an important research *** researchers have proposed techniques to predict this disease through data mining and machine learning *** prediction,feature selection is a key concept in ***,the features that are relevant to the disease are used for *** condition improves the prediction *** the right features in the whole feature set is a complicated process,and many researchers are concentrating on it to produce a predictive model with high *** this work,a wrapper-based feature selection method called recursive feature elimination is combined with ridge regression(L2)to form a hybrid L2 regulated feature selection algorithm for overcoming the overfitting problem of data *** is a major problem in feature selection,where the new data are unfit to the model because the training data are *** regression is mainly used to overcome the overfitting *** features are selected by using the proposed feature selection method,and random forest classifier is used to classify the data on the basis of the selected *** work uses the Pima Indians Diabetes data set,and the evaluated results are compared with the existing algorithms to prove the accuracy of the proposed *** accuracy of the proposed algorithm in predicting diabetes is 100%,and its area under the curve is 97%.The proposed algorithm outperforms existing algorithms.
Pupil dynamics are the important characteristics of face spoofing *** face recognition system is one of the most used biometrics for authenticating individual *** main threats to the facial recognition system are diff...
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Pupil dynamics are the important characteristics of face spoofing *** face recognition system is one of the most used biometrics for authenticating individual *** main threats to the facial recognition system are different types of presentation attacks like print attacks,3D mask attacks,replay attacks,*** proposed model uses pupil characteristics for liveness detection during the authentication *** pupillary light reflex is an involuntary reaction controlling the pupil’s diameter at different light *** proposed framework consists of two-phase *** the first phase,the pupil’s diameter is calculated by applying stimulus(light)in one eye of the subject and calculating the constriction of the pupil size on both eyes in different video *** above measurement is converted into feature space using Kohn and Clynes model-defined *** Support Vector Machine is used to classify legitimate subjects when the diameter change is normal(or when the eye is alive)or illegitimate subjects when there is no change or abnormal oscillations of pupil behavior due to the presence of printed photograph,video,or 3D mask of the subject in front of the *** the second phase,we perform the facial recognition ***-invariant feature transform(SIFT)is used to find the features from the facial images,with each feature having a size of a 128-dimensional *** features are scale,rotation,and orientation invariant and are used for recognizing facial *** brute force matching algorithm is used for matching features of two different *** threshold value we considered is 0.08 for good *** analyze the performance of the framework,we tested our model in two Face antispoofing datasets named Replay attack datasets and CASIA-SURF datasets,which were used because they contain the videos of the subjects in each sample having three modalities(RGB,IR,Depth).The CASIA-SURF datasets showed an 89.9%Equal Err
Time series data is fundamentally important for many critical domains such as healthcare, finance, and climate, where explainable models are necessary for safe automated decision-making. To develop explainable artific...
The paper presents the rotated 3D-printed dielectric lens assembly with an ultra-wideband (UWB) antenna for use in the beam-steering applications. The focus is on achieving beam steering by combining the rotated 3D-pr...
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As the number of cores in a multicore system increases,the communication pressure on the interconnection network also *** network-on-chip(NoC)architecture is expected to take on the ever-expanding communication demand...
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As the number of cores in a multicore system increases,the communication pressure on the interconnection network also *** network-on-chip(NoC)architecture is expected to take on the ever-expanding communication demands triggered by the ever-increasing number of *** communication behavior of the NoC architecture exhibits significant spatial–temporal variation,posing a considerable challenge for NoC *** this paper,we propose a traffic-oriented reconfigurable NoC with augmented inter-port buffer sharing to adapt to the varying traffic flows with a high ***,a modified input port is introduced to support buffer sharing between adjacent ***,the modified input port can be dynamically reconfigured to react to on-demand ***,it is ascertained that a centralized output-oriented buffer management works well with the reconfigurable input ***,this reconfiguration method can be implemented with a low overhead hardware design without imposing a great burden on the system *** experimental results show that compared to other proposals,the proposed NoC architecture can greatly reduce the packet latency and improve the saturation throughput,without incurring significant area and power overhead.
This paper deals with the design of a novel Active Fault Tolerant Control (AFTC) algorithm for an underactuated quadrotor UAV system in the presence of actuator faults. A robust control strategy based on the backstepp...
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With the ever-expanding ubiquity of the Internet, wireless networks have permeated every facet of modern life, escalating concerns surrounding network security for users. Consequently, the demand for a robust Intrusio...
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Body fitness monitoring applications are using mobile sensors to identify human activities. Human activity identification is a challenging task because of the wide availability of human activities. This paper proposes...
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The integration of Artificial Intelligence(AI) with Long-Term Evolution (LTE) networks offers substantial potential for improving communication infrastructure. By harnessing AI algorithms, it is possible to dynamicall...
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ISBN:
(数字)9798331527396
ISBN:
(纸本)9798331527402
The integration of Artificial Intelligence(AI) with Long-Term Evolution (LTE) networks offers substantial potential for improving communication infrastructure. By harnessing AI algorithms, it is possible to dynamically optimize network parameters, proactively predict and mitigate equipment failures, and enhance Quality of Service (QoS) by prioritizing critical services through real-time analysis of key performance indicators. This study focuses on predicting network throughput using Least Square Support Vector Machine (LS-SVM). The predictive models developed can trigger adaptive network reconfigurations, ensuring that the network responds promptly to changing conditions. Simulation results reveal that the integration of LS-SVM significantly improves prediction accuracy, enabling more effective implementation of self-organizing network strategies in real-time.
This study explores the utility of Support Vector Machines (SVM) for the classification of injuries in Athletes including tennis, table tennis, and badminton. The primary objective of this research was to develop an a...
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